![]() This is consistent with the data set providing a detailed picture of the proteins expressed in these cells. ![]() While the median sequence coverage across the entire data set was ~36.5% per protein, this rose to >95% for many of the most abundant proteins (įigure 2D). ![]() First, we compared how protein sequence coverage was affected by protein copy number (see below for discussion of copy number estimations). To investigate further how comprehensively our present data set describes the human epithelial cell proteome, we evaluated the depth of proteome coverage using several approaches. Collectively, these findings suggest that a differentiated human cell may typically express at the protein level up to ~70% of the protein coding genes in the human genome. This level of coverage is comparable to recent deep proteome analyses reported for transformed human cell lines, e.g. The protein groups identified by MS analysis represent ~55% of the reference SwissProt total human proteome (see Methods). Overview of the epithelial proteome in untransformed cellsįirst, we characterised the proteome of untransformed epithelial cells with respect to protein expression and protein turnover. We identified >10,000 protein groups at each of the seven time-points analysed after v-Src activation (įigure 2C). Most of the protein groups were identified in both the time course (Exp A) and protein turnover (Exp B) experiments (cf.įigure 2A), with 966 and 1,562 protein groups exclusively detected in Exp A and Exp B, respectively (įigure 2C). For further discussion of the numbers of proteins and isoforms expressed and methods for estimating integrated protein false discovery rates (FDR), see Methods. These peptides were mapped to ~13,900 protein groups, with a median protein sequence coverage of ~36% per protein (įigure 2C). Analysis of the spectra (see Methods for details) resulted in >19 million peptide spectrum matches (PSMs), which identified >350,000 unique peptides (including post translationally modified peptides), with >200,000 corresponding to unique, unmodified peptide sequences. In total, >33 million MS1 spectra and >95 million MS2 spectra were acquired. ![]() ProteomeXchange PRIDE repository (PRIDE accession Log rank test p 2,000 raw MS files, all of which are freely available via the Kaplan-Maier curves for patients showing the top (green dashed line) and bottom (red dotted line) third signal are plotted. Active Src kinase is a predictor of poor clinical outcome.Ĭartoon schematics illustrating the development of metastatic phenotypes (Ī), and the Src-ER model system for oncogenesis (Ĭ) The Cancer Genome Atlas patients were stratified into three cohorts based on reverse phase protein array intensities for pSrc-Y416. by viral expression of oncogenes, such as v-Src ( Such profound changes in gene expression can be triggered endogenously by the mutation of proto-oncogenes and tumour suppressors, and/or exogenously, e.g. including the abundance, post-translational modification, half-life and/or activity, of specific subsets of proteins that mediate the metastatic phenotypes. This is reflected in corresponding changes in patterns of gene expression in the transformed cells, leading to changes in the ‘properties’, e.g. These include increased motility and invasion, migration and immune cell evasion phenotypes, which are not active in the healthy differentiated cells. Hanahan & Weinberg, 2011), are associated with late stage development of cancer and strongly linked with poor clinical outcomes for patients. Advanced forms of malignancy that are associated with poor clinical outcomes, including high-grade breast and oesophageal tumours, are characterized by tumour invasion into the surrounding stroma (illustrated inįigure 1A) and the development of metastases at sites distal to the initial tumour. World epg xml.Cancer malignancies have in common the development of cellular phenotypes that alter the normal behaviour of the respective terminally differentiated cell types.
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